The present disclosure is related to the field of automated transcription. More specifically, the preset disclosure is related to diarization using linguistic labeling.
Speech transcription and speech analytics of audio data may be enhanced by a process of diarization wherein audio data that contains multiple speakers is separated into segments of audio data typically to a single speaker. While speaker separation in diarization facilitates later transcription and/or speech analytics, further identification or discrimination between the identified speakers can further facilitate these processes by enabling the association of further context and information in later transcription and speech analytics processes specific to an identified speaker.
Systems and methods as disclosed herein present solutions to improve diarization using linguistic models to identify and label at least one speaker separated from the audio data.